{ “@context”: “http://schema.org”, “@type”: “JobPosting”, “title”: “Senior Data Scientist (Frontier)”, “description”: “
Requirements
- You have senior-level experience in data science or quantitative research
- You’re proficient in Python and essential libraries (NumPy, Pandas, scikit-learn), plus familiarity with a deep-learning framework (e.g., TensorFlow, PyTorch)
- You possess a strong foundation in statistics and mathematics
- You’re experienced across the full data science toolkit—including supervised/unsupervised learning, time‑series, Bayesian methods, and model validation—and can develop new algorithms when needed
- You bring a leadership mindset centred on technical excellence, team growth, and a collaborative culture
- You exhibit scientific rigor and a business-focused approach: translating problems into technical strategies and measuring model impact
- You’re product‑oriented, deeply understanding user needs and how Frontier can deliver value to them
- It would be great if you had experience building and evaluating agents using eval‑driven development (although not a must‑have)
- If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don’t hesitate in applying as you might be right for this role, or other role
What the job involves
- Join the Frontier team to shape the future of our Decision Intelligence Platform by delivering AI‑powered digital twins that elevate organisational decision‑making
- As a Senior Data Scientist, solving highly complex and consequential problems and helping enterprise users interact with cutting‑edge AI. This is a unique, entrepreneurial role where you will drive real value by combining scientific rigor with a business‑focused approach to advance our AI Agent and Decision Hub capabilities
- Designing and building agents in high‑consequence environments, where outputs need to be validated to a high standard
- Performing exploratory data analysis, model building, validation, and performance monitoring
- Leading data science efforts within cross‑functional delivery teams—partnering with engineers, designers, and product leads for successful outcomes
- Understanding deeply core customer problems to ensure technical solutions drive real value
- Translating real‑world problems into technical strategies and measuring model impact with scientific rigor
Company: Deepstreamtech
Location: London
Job Description:
Requirements
- You have senior-level experience in data science or quantitative research
- You’re proficient in Python and essential libraries (NumPy, Pandas, scikit-learn), plus familiarity with a deep-learning framework (e.g., TensorFlow, PyTorch)
- You possess a strong foundation in statistics and mathematics
- You’re experienced across the full data science toolkit—including supervised/unsupervised learning, time‑series, Bayesian methods, and model validation—and can develop new algorithms when needed
- You bring a leadership mindset centred on technical excellence, team growth, and a collaborative culture
- You exhibit scientific rigor and a business-focused approach: translating problems into technical strategies and measuring model impact
- You’re product‑oriented, deeply understanding user needs and how Frontier can deliver value to them
- It would be great if you had experience building and evaluating agents using eval‑driven development (although not a must‑have)
- If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don’t hesitate in applying as you might be right for this role, or other role
What the job involves
- Join the Frontier team to shape the future of our Decision Intelligence Platform by delivering AI‑powered digital twins that elevate organisational decision‑making
- As a Senior Data Scientist, solving highly complex and consequential problems and helping enterprise users interact with cutting‑edge AI. This is a unique, entrepreneurial role where you will drive real value by combining scientific rigor with a business‑focused approach to advance our AI Agent and Decision Hub capabilities
- Designing and building agents in high‑consequence environments, where outputs need to be validated to a high standard
- Performing exploratory data analysis, model building, validation, and performance monitoring
- Leading data science efforts within cross‑functional delivery teams—partnering with engineers, designers, and product leads for successful outcomes
- Understanding deeply core customer problems to ensure technical solutions drive real value
- Translating real‑world problems into technical strategies and measuring model impact with scientific rigor
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Posted: May 19th, 2026